An application runs on Amazon EC2 instances across multiple Availability Zones in an Auto Scaling group behind an Application Load Balancer. The application performs best when EC2 CPU utilization is near 40%. What should a solutions architect do to maintain this performance across all instances in the group?
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Correct answer: Use a target tracking policy to dynamically scale the Auto Scaling group..
Why this is the answer
A target tracking policy is the most effective solution here because it automatically adjusts the Auto Scaling group's capacity to maintain a specified metric (in this case, CPU utilization) at a target value (40%). This ensures optimal performance without manual intervention. Simple scaling policies react to breaches of thresholds but don't actively maintain a target. AWS Lambda functions could update capacity, but this is a more complex, custom solution compared to the built-in target tracking. Scheduled scaling actions are for predictable load changes, not for maintaining a dynamic performance metric like CPU utilization.
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